Methodology Reference · Macro Dashboards

China Financial Conditions Index

A weekly read on how loose or tight Chinese financial conditions are — built from eight market series, reported as two complementary indices. Unlike a rates-only gauge, it deliberately layers in property and a credit impulse, so it reflects the channels that actually drive China's cycle. Lower always means looser.

◄ looser (easing) neutraltighter (stress) ►

Two indices, one engine

Both indices use the same eight components, the same signs, and the same category weights. They differ in one thing only: whether each series is standardized against a fixed historical base or a rolling window.

FCI — LEVEL

Goldman-style, anchored at 100

Weighted sum of component levels, standardized on the full 2018-present sample and anchored so the base-period average = 100. Preserves secular drift.

▸ "How loose/tight vs the post-2018 sample?"

FCI — MOMENTUM

Rolling 52-week z-score

Identical construction, but moments come from a trailing 52-week window. Detrended, centred near zero.

▸ "Have conditions tightened vs the last year?"

Read them together. A typical week might say "the level is modestly loose, but momentum is tightening" — easy in absolute terms (rates at record lows), yet tightening at the margin as property and credit roll over.

Components & weights

Eight series in five categories. The sign encodes a growth-impulse convention: +1 means a higher value tightens conditions (raises the index); −1 means a higher value loosens them (lowers it).

Series	Category	Cat wt	Sub wt	Sign	Higher value →
CFETS RMB Index	FX	0.10	0.50	+1	stronger RMB → tighter
BIS broad REER	FX	0.10	0.50	+1	stronger real RMB → tighter
SHCOMP trend gap (200d)	Equity	0.20	0.50	−1	above trend → looser
SHCOMP realised vol (21d)	Equity	0.20	0.50	+1	higher vol → tighter
3M SHIBOR	Rates	0.20	0.50	+1	higher → tighter
CGB 10Y yield	Rates	0.20	0.50	+1	higher → tighter
70-city 2nd-hand YoY	Property	0.20	1.00	−1	faster → looser
TSF credit impulse	Credit	0.30	1.00	−1	accelerating → looser

Category weights sum to 1.00; sub-weights sum to 1.00 within each category. Equal-weight (0.20 each) is the validation benchmark; FX is cut to 0.10 (a managed float carries little information) and the freed weight routed to the credit impulse.

How it's built

1 · Sign & standardize

Each raw series is signed and standardized to zero mean, unit variance:

x_i,t = sign_i × ( X_i,t − μ_i ) / σ_i

The moments (μ, σ) are the only switch between the two indices — the full 2018-present sample for the Level, a trailing 52-week window for Momentum.

2 · Category composites

Multi-series categories (FX, Equity, Rates) are combined by sub-weight, then re-standardized to unit variance — without this step, averaging correlated sub-series shrinks the category's variance and silently under-weights it.

fx     = standardize( 0.5·x_cfets  + 0.5·x_reer )
equity = standardize( 0.5·x_gap    + 0.5·x_vol )
rates  = standardize( 0.5·x_shibor + 0.5·x_cgb10y )

3 · Weight & aggregate

C_t = 0.10·FX + 0.20·Equity + 0.20·Rates + 0.20·Property + 0.30·Credit

4 · Anchor

Level     :  FCI = 100 + (1 / SD_base(C)) × C_t
Momentum  :  FCI = C_t          (rolling moments)

This anchoring is our own scaling choice: because the deviation is divided by the composite's full-sample standard deviation, one index point equals one base-period SD by construction — so 98 is ~2 SD looser than the post-2018 average and 102 ~2 SD tighter. It is the same SD scale the commentary uses when it cites, e.g., "−0.1 SD". Note this is not how Goldman scales its headline index (see §06). Master frequency is weekly (Friday); daily series are sampled last-obs, monthly series (property, credit) forward-filled with no interpolation.

Sign conventions growth-impulse

Signs follow the logic that asset-price and credit strength is stimulative — broadly the framing Goldman uses. This is a deliberate choice; it makes the index a read on the growth impulse from conditions, not a froth/stress gauge.

Weak RMB → looser. A weaker trade-weighted RMB supports an export economy, so it eases conditions. (Strong RMB → tighter.) The RMB is a managed float, so it moves little and in administered steps — hence FX carries the lowest weight.
Equities above trend → looser via the wealth effect and cheaper equity capital. China's household equity-wealth share is low (most wealth is in property), so equity is a smaller channel here than in the US.
Equity volatility → tighter. Elevated vol signals stress — and deliberately offsets the trend gap (see §6).
Higher SHIBOR / 10Y CGB → tighter (higher cost of capital). The short end (SHIBOR) is liquidity-driven; the long end (CGB) is the cost-of-capital anchor.
Faster house-price growth → looser via collateral and wealth. The 70-city second-hand series is used rather than new-home prices, which are partly administered/floored — 2nd-hand is the cleaner market signal.
Accelerating credit → looser. The TSF credit impulse is the single most important China financial-conditions variable; in China, policy transmits through the quantity of credit, not its price.

Flip note. Inverting the equity-gap, property and credit signs turns this into a stress/overheating index instead — a different question. Keep the growth-impulse signs consistent.

Reading the dashboard

FCI — Level (top): the headline. Green below 100 = looser than the post-2018 norm, red above = tighter.
Category contribution (directly beneath): decomposes the current Level into its five category contributions — green easing, red tightening. This explains the chart above it.
FCI — Momentum: the rolling z-score. The shaded grey band marks the trailing 52-week window the current z is measured over.
Component tiles: each raw series over its last 52 weeks, with a signed z-badge (green easing / red tightening) measured versus the last year. The SHCOMP tile shows its 52-week price gain.

The tiles (vs the last year) and the Level contributions (vs the whole sample) can disagree — a component can sit near its post-2018 average yet be tightening hard against the last twelve months. That gap is exactly what the Momentum index captures.

Relationship to Goldman's FCI

The Level index is built on the methodology Goldman set out in Our New G10 Financial Conditions Indices (Goldman Sachs Global Economics, 2017): a weighted average of a short rate, a long-term yield, a credit measure, an equity-price variable and a trade-weighted exchange rate, with weights reflecting each variable's estimated effect on GDP growth over a one-year horizon.

This index departs from Goldman's daily China FCI in two deliberate ways. First, it adds a property channel and a TSF credit-impulse channel — together 50% of the weight — which the daily GS index omits. Second, the equity leg uses a trend gap plus a realised-vol overlay rather than a valuation (Shiller-style) input. The upshot: when the property/credit cycle is weak, this Level reads meaningfully less tight than a rates-dominated GSCNFCI, because half the index sits on the downturn channels that offset easy money.

Weights here are share-based and standardized, not Goldman's proprietary GDP-impact coefficients. The shapes co-move; the absolute levels are not expected to match tick-for-tick.

Sign-convention check. Before reconciling against a published series, mind the direction: GS's FCI is higher = tighter, while Bloomberg's CHBGFCI is higher = looser — the opposite convention to each other.

On units. Our Level expresses deviations in post-2018 standard deviations (1 point = 1 SD; see §03). Goldman's headline index is instead scaled to growth impact — a one-point move corresponds to roughly one percentage point of year-ahead GDP growth — so its "points" are not standard deviations. Standardized, SD-based presentations of the GS FCI do exist (the BIS, for example, publishes it as 100 = long-run average with each unit a one-SD move), and our scale matches that convention rather than the paper's native growth-impact units.

Data & refresh

The authoritative history is a Bloomberg export. For the weekly run, the tail is extended to the latest date from free sources where a clean feed exists, level-matched onto the Bloomberg series:

SHCOMP — Yahoo Finance ^SSEC (→ Stooq fallback)
REER — FRED RBCNBIS (BIS broad, no key)
CGB 10Y, 3M SHIBOR — AkShare (best-effort; flaky from Singapore, so these carry forward when the source doesn't answer)
70-city 2nd-hand prices & the TSF credit impulse — carried forward from Bloomberg (monthly and lagged; refreshed by the weekly re-export)

Why the thin live layer. China has no clean, freely accessible daily feed for its rate, property and credit series from outside the mainland — there is no Bank-of-Korea-ECOS equivalent. The Bloomberg re-export is therefore the authoritative refresh; the live tail mainly keeps the equity and FX legs current between exports.

Published weekly, Friday morning (06:30 SGT), to Discord with an auto-generated commentary.

Caveats

Short sample (2018→). Bloomberg's TSF stock series begins Jan-2017 (a PBoC rebasing); the 12-month credit impulse off it is first valid Jan-2018 and binds the whole common sample. A frozen pre-period "normal" like the Korea build isn't available — the Level uses a full-sample base instead. Swapping the credit channel to M2 YoY would extend history to ~2009 at the cost of a narrower credit definition.
Credit impulse is a second derivative — the change of a growth rate, so inherently noisy. At 0.30 weight it can whip Momentum around; winsorising it or dialling the weight to 0.25 is a one-line change if needed.
GDP-free impulse. The canonical China credit impulse is new credit flow as a share of nominal GDP. With no GDP series in the pull, this uses the acceleration of TSF YoY growth as a monotone proxy; add quarterly nominal GDP to recover the % -of-GDP version.
Managed FX. The RMB moves in policy-guided steps, so its information content is low — don't over-read FX contributions (hence the 0.10 weight).
Property is lagged, monthly & partly administered — don't over-read week-to-week housing moves.
Mixed frequency. Property + credit (50% of weight) are monthly; the index's week-to-week movement is driven by the daily half (FX / equity / rates), with the macro half stepping once a month.
Structural breaks (the 2018 trade war, COVID, the 2021–22 property crisis, the 2023–24 deflation scare) distort any fixed base and short rolling window; inspect component z-scores around these dates.

References

Goldman Sachs Global Economics. Our New G10 Financial Conditions Indices, Global Economics Analyst, 20 April 2017. gspublishing.com

Bank for International Settlements. Effective exchange rate indices (REER, broad) and residential property price statistics.

People's Bank of China. Total Social Financing aggregates and SHIBOR; National Bureau of Statistics — 70-city residential price indices; ChinaBond — government-bond yield curve.